Probability Item Bundles Adjusting Distribution Probabilities via User Spending Metrics
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Solution Overview
Problem
Conventional systems do not adjust the distribution probabilities of potential awards in probability item bundles based on the purchase history of users, failing to provide personalized and dynamic reward structures in virtual game spaces.
Innovation Solution
A system that tracks and quantifies user purchase histories into spending metrics, using these metrics to dynamically adjust distribution probabilities for individual potential awards within probability item bundles, allowing for stochastic selection of actual awards based on user spending behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If distribution probabilities of potential awards are fixed in probability item bundles, then system simplicity is maintained, but user personalization and engagement are reduced
Solution Approach 1:
The patent implements dynamic distribution probabilities that automatically adjust based on user purchase history. The system transitions from static fixed probabilities to dynamic probabilities that change over time based on user behavior, allowing the reward structure to adapt to individual users without manual intervention.
Solution Approach 2:
The system incorporates feedback loops where user purchase history is continuously monitored and fed back into the probability calculation mechanism. This feedback enables the system to learn from user behavior patterns and adjust distribution probabilities accordingly, creating a personalized experience while maintaining automated operation.
2Productivity
If distribution probabilities are adjusted based on purchase history, then user engagement and personalization improve, but system complexity and data processing requirements increase
Solution Approach 1:
The system performs preliminary actions by continuously tracking and storing user purchase history data in advance. This pre-processing of user behavior data enables the probability adjustment mechanism to operate efficiently when users activate probability item bundles, as the necessary historical data is already prepared and organized.
Solution Approach 2:
The patent changes the parameter of distribution probabilities from fixed values to variable values that depend on purchase history metrics. This parameter transformation allows the system to personalize user experiences by modifying probability parameters based on observed user behavior patterns.
Data Source
AI summary
A system and method for varying the distribution probabilities of individual potential awards associated with probability item bundles depending on a purchase history of a user activating a probability item bundle.